metadata

title: Linkedin Assistant
emoji: 🚀
colorFrom: red
colorTo: red
sdk: docker
app_port: 8501
tags:
  - streamlit
pinned: false
short_description: Streamlit template space
license: mit

🤖 LinkedIn AI Career Assistant

An intelligent AI-powered career assistant that analyzes LinkedIn profiles, provides job fit analysis, and offers personalized career guidance through an interactive chat interface powered by Groq's llama3-8b-8192 model.

🚀 Live Demo

Try the application live at: https://sri-vallabh-linkedin-profile-ai-assistant-app-ffuh1c.streamlit.app/

🎯 Overview

The LinkedIn AI Career Assistant is a sophisticated career optimization tool that combines Groq's powerful llama3-8b-8192 model with LangGraph's multi-agent framework to provide comprehensive LinkedIn profile analysis. Built using Streamlit, LangGraph, and Groq API, this application offers an interactive chat-based experience for professional career development.

What Makes This Special?

🧠 Multi-Agent AI System: Utilizes LangGraph to orchestrate specialized AI tools for different analysis tasks
💾 Thread-Based Sessions: Maintains conversation context with intelligent thread management based on LinkedIn URLs
🎯 Job Fit Analysis: Provides detailed match scores and improvement suggestions for target roles
📊 Profile Analysis: Comprehensive strengths and weaknesses assessment
🔄 Real-time Scraping: Fetches live LinkedIn profile data using Apify integration
⚡ Groq-Powered: Lightning-fast responses using Groq's optimized llama3-8b-8192 model

🌟 Key Features

1. Interactive Chat Interface

LinkedIn URL Input: Simply paste your LinkedIn profile URL to get started
Conversational AI: Natural language interaction for profile optimization
Real-time Analysis: Instant feedback and suggestions as you chat
Custom Styling: Modern chat bubble interface with professional design

2. Comprehensive Profile Analysis

Strengths Identification: Highlights technical skills, projects, education, and soft skills
Weakness Detection: Identifies gaps in technical skills, experience, and missing context
Actionable Suggestions: Provides specific recommendations for profile enhancement
Section-by-Section Access: Detailed extraction of individual LinkedIn profile sections

3. Advanced Job Fit Analysis

Match Score Calculation: Quantifies how well your profile fits target roles (0-100%)
Skill Gap Analysis: Identifies missing skills required for your target position
Role-Specific Feedback: Tailored suggestions for improving job compatibility
Visual Score Display: Circular progress indicators for match percentages

4. Intelligent Session Management

URL-Based Threading: Automatically finds existing conversations for the same LinkedIn profile
Session Continuity: Choose to continue previous chats or start fresh
SQLite Persistence: Robust conversation storage with automatic checkpointing
Thread Isolation: Secure separation of different user sessions

5. Professional Data Handling

Pydantic Validation: Robust data validation using structured schemas
State Management: Comprehensive state tracking across conversation flows
Error Handling: Graceful handling of API failures and data parsing issues
Memory Optimization: Efficient storage and retrieval of conversation context

🏗️ Architecture

Multi-Agent System Design

┌─────────────────────────────────────────────────────────────┐
│                    User Interface (Streamlit)               │
│                     Custom Chat Interface                   │
└─────────────────────┬───────────────────────────────────────┘
                      │
┌─────────────────────┴───────────────────────────────────────┐
│                   LangGraph Orchestrator                    │
│                    (ChatbotState Schema)                    │
│  ┌─────────────────┬─────────────────┬─────────────────┐    │
│  │   Chatbot Node  │  Profile Tool   │  Job Match Tool │    │
│  │   (Router)      │   (Analyzer)    │   (Matcher)     │    │
│  │                 │                 │                 │    │
│  │  Extract Tool   │                 │                 │    │
│  │  (Section Data) │                 │                 │    │
│  └─────────────────┴─────────────────┴─────────────────┘    │
└─────────────────────┬───────────────────────────────────────┘
                      │
┌─────────────────────┴───────────────────────────────────────┐
│                    External Services                        │
│  ┌─────────────────┬─────────────────┬─────────────────┐    │
│  │  Apify LinkedIn │    Groq API     │   SQLite        │    │
│  │    Scraper      │ (llama3-8b-8192)│  Checkpointer   │    │
│  └─────────────────┴─────────────────┴─────────────────┘    │
└─────────────────────────────────────────────────────────────┘

Core Components

ChatBot Node: Main conversation router with tool calling capabilities
Profile Analyzer: Comprehensive profile evaluation for strengths and weaknesses
Job Matcher: Role compatibility analysis with scoring and suggestions
Extract Tool: Granular access to specific profile sections
State Management: Pydantic-based ChatbotState with comprehensive field tracking
Thread System: URL-based session identification and management

🛠️ Installation

Prerequisites

Python 3.8 or higher
pip package manager
Groq API key
Apify API token

Quick Start

Clone the Repository

git clone https://github.com/Sri-Vallabh/Linkedin-Profile-AI-Assistant.git
cd Linkedin-Profile-AI-Assistant

Install Dependencies

pip install -r requirements.txt

Set Up Environment Variables

cp .env.example .env
# Edit .env with your API keys

Run the Application

streamlit run app.py

Access the Application

Open your browser and go to: http://localhost:8501

Requirements

streamlit>=1.28.0
langchain>=0.0.350
langchain-openai>=0.0.8
langgraph>=0.0.55
openai>=1.3.0
pydantic>=2.0.0
python-dotenv>=1.0.0
apify-client>=1.0.0
dirtyjson>=1.0.8

📖 Usage

Getting Started

Launch the Application
- Open the application in your browser
- You'll see the main interface with a LinkedIn URL input field
Enter Your LinkedIn Profile
- Paste your LinkedIn profile URL (e.g., https://www.linkedin.com/in/your-profile/)
- The system will automatically scrape and analyze your profile
Choose Session Mode
- If a previous session exists, choose to continue or start fresh
- New sessions initialize with full profile preprocessing
Start Chatting
- Begin conversations with queries like:
  - "Analyze my profile strengths and weaknesses"
  - "I want to apply for a Data Scientist role"
  - "Show me my about section"
  - "What skills am I missing for a Software Engineer position?"

Available Commands

Profile Analysis: "Analyze my profile" - Full strengths/weaknesses analysis
Job Matching: "I want to apply for [role]" - Match score and skill gaps
Section Access: "Show me my [section]" - Extract specific profile sections
General Queries: Ask any career-related questions for guidance

Sample Conversations

User: "Analyze my LinkedIn profile"
AI: ✅ Profile analysis complete!

💪 Strengths
- Technical: Python, Machine Learning, Data Analysis
- Projects: E-commerce recommendation system, Stock prediction model
- Education: Computer Science degree, Data Science certification
- Soft Skills: Problem-solving, Team collaboration

⚠️ Weaknesses
- Technical Gaps: Cloud computing platforms, MLOps tools
- Project/Experience Gaps: Limited production deployment experience
- Missing Context: Quantified project impacts and metrics

🛠 Suggestions to improve
- Add AWS/Azure cloud certifications
- Include specific metrics for project outcomes
- Highlight leadership or mentoring experiences

User: "I want to apply for a Senior Data Scientist role"
AI: 📊 Job Fit Analysis

🎯 Target Role: Senior Data Scientist
Match Score: 78%

Missing Skills:
• Deep Learning frameworks (TensorFlow, PyTorch)
• MLOps and model deployment
• Leadership and team management experience

Suggestions:
• Complete online courses in deep learning
• Build projects showcasing end-to-end ML pipelines
• Seek opportunities to lead junior team members

🔧 Technical Implementation

State Management

The application uses a sophisticated Pydantic-based state management system:

class ChatbotState(BaseModel):
    profile: Dict[str, Any]  # Processed LinkedIn profile data
    profile_url: Optional[str]  # Original LinkedIn URL
    sections: Dict[str, str]  # Individual profile sections
    enhanced_content: Dict[str, str]  # Future AI-generated improvements
    profile_analysis: Optional[Dict[str, Any]]  # Strengths/weaknesses
    job_fit: Optional[Dict[str, Any]]  # Job matching results
    target_role: Optional[str]  # User's target job role
    messages: Annotated[List[BaseMessage], add_messages]  # Chat history
    next_tool_name: Optional[str]  # Tool routing information

Tool Integration

The system includes three specialized tools:

Profile Analyzer Tool:
- Comprehensive profile evaluation
- Structured output with strengths, weaknesses, suggestions
- Uses ProfileAnalysisModel for validation
Job Matcher Tool:
- Role-specific compatibility analysis
- Calculates match scores (0-100%)
- Identifies missing skills and provides suggestions
Extract Tool:
- Granular access to profile sections
- Supports nested data extraction with dot notation
- Returns structured results for specific queries

Session Architecture

Thread Management: URL-based thread identification for session continuity
Checkpointing: SQLite-based persistent storage with automatic fallback
State Validation: Comprehensive Pydantic validation for data integrity
Memory Optimization: Efficient message history management

LLM Integration

Model: Groq's llama3-8b-8192 for fast, high-quality responses
API: OpenAI-compatible interface through Groq
Tool Calling: Native support for structured tool invocation
Error Handling: Robust retry mechanisms and graceful degradation

🔑 API Keys Setup

Create a .env file in the root directory:

# Groq API Key (required)
GROQ_API_KEY=your_groq_api_key_here

# Apify API Token (required for LinkedIn scraping)
APIFY_API_TOKEN=your_apify_token_here

Getting API Keys

Groq API Key:
- Visit Groq Console
- Create an account and generate an API key
- Used for llama3-8b-8192 model inference
Apify API Token:
- Go to Apify Console
- Sign up and get your API token
- Used for LinkedIn profile scraping

💾 Session Management

The application implements intelligent session management:

Thread-Based System

Each LinkedIn profile URL gets a unique thread ID
Automatic detection of existing conversations for the same profile
Secure isolation between different user sessions

Conversation Persistence

SQLite-based storage for production environments
Memory-based fallback for development/testing
Automatic checkpointing after each interaction
Recovery capability in case of interruptions

User Experience

Choice to continue previous conversations or start fresh
Seamless transition between sessions
Maintained conversation context across browser refreshes

🤝 Contributing

We welcome contributions to improve the LinkedIn AI Career Assistant! Here's how you can help:

Development Setup

Fork the repository
Create a feature branch: git checkout -b feature/your-feature-name
Make your changes and test thoroughly
Submit a pull request with a clear description

Areas for Contribution

Tool Enhancement: Implement the commented-out content_generator tool
UI/UX Improvements: Enhance the Streamlit interface design
Performance Optimization: Improve response times and resource usage
Testing: Add comprehensive test coverage
Documentation: Expand examples and API documentation

Code Style

Follow PEP 8 guidelines for Python code
Use meaningful variable and function names
Add docstrings for all functions and classes
Include type hints where appropriate
Validate data models with Pydantic

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

Groq for providing fast and efficient LLM inference
LangChain/LangGraph for the multi-agent framework
Streamlit for the web application framework
Apify for LinkedIn scraping capabilities
Hugging Face for hosting the live demo

📞 Support

For questions, issues, or suggestions:

Create an Issue: GitHub Issues
Discussions: GitHub Discussions
Email: tsrivallabh2014@gmail.com

🔄 Recent Updates

v2.0: Migrated to Groq API for faster inference
Thread Management: Implemented URL-based session tracking
Enhanced UI: Custom chat interface with professional styling
Robust State: Pydantic-based data validation and error handling
Tool Optimization: Streamlined to three core analysis tools

Built with ❤️ by Sri Vallabh

Empowering professionals to optimize their LinkedIn presence and advance their careers through AI-powered insights.